Neuron: Offline Cognitive AI

Neuron is an architecture for an artificial intelligence that runs fully offline. It combines perception, memory, emotion, logic and control in separate modules: it perceives the surrounding world through a camera and a microphone, remembers past requests, reacts with a personality and takes decisions.

The project grew out of work on face and voice recognition and out of the research interest in offline AI architecture with memory and adaptive behaviour. A physical body controlled through Arduino is one of its goals.

Face recognition project

Category :Cognitive AI Architecture
Stack :Python (PyTorch, FastAPI declared)
Modules :Perception, memory, emotion, logic, central control
Language model :Tokenizer, embeddings, transformer blocks, next-word output
Physical control :Arduino body
Mode :Offline
Status :Architecture stage
Source :GitHub repository

Neuron brain-shaped neural network with five modules

Core Features

The point of the architecture is separation of responsibility: each ability lives in its own module and talks to the others through a central control unit.

Perception module for camera and microphone input.
Memory module that stores past requests and experience.
Emotion module that generates reactions and personality.
Logic module for decision making.
Central control module that coordinates all subsystems.
Offline operation without a cloud dependency.

“Modular architecture, offline operation, memory and a body: the goals are listed before the code.”

Design Note - Architecture First

Architecture

The diagram shows how the modules interact: perception feeds memory and emotion, while the central control unit coordinates logic and decision modules and produces the output. The text path uses a standard language-model chain: tokenizer, embedding layer, many transformer blocks, then a linear layer with softmax for the next word. The project is at the architecture stage: the structure is defined and implementation is in progress.